finish fine-tuning

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README.md

@@ -1,3 +1,87 @@
 ---
 license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- samsum
+metrics:
+- rouge
+model-index:
+- name: flan-t5-large-samsum
+  results: []
+datasets:
+- samsum
+language:
+- en
+pipeline_tag: summarization
 ---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# flan-t5-large-samsum
+
+This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the samsum dataset.
+
+It achieves the following results on the evaluation set:
+- Loss: 1.1754
+- Rouge1: 54.1595
+- Rouge2: 29.1081
+- Rougel: 45.4989
+- Rougelsum: 49.1026
+- Gen Len: 28.72
+
+> Note: the stacked version of this model technically does evaluation on a **different** validation set (the stacked one) while this just uses `samsum`.
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+- Intended for comparison(s) to the [stacked version of this model](https://huggingface.co/stacked-summaries/flan-t5-large-stacked-samsum-1024)
+- 1024 token input max
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 8
+- eval_batch_size: 4
+- seed: 17868
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.04
+- num_epochs: 5.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
+| 1.2106        | 0.43  | 50   | 1.1889          | 52.5898 | 26.9967 | 43.6944 | 47.9656   | 24.5167 |
+| 1.213         | 0.87  | 100  | 1.1760          | 52.4279 | 27.4689 | 43.7873 | 48.0581   | 25.0533 |
+| 1.0726        | 1.3   | 150  | 1.1731          | 52.8246 | 26.9524 | 43.7429 | 48.0345   | 25.55   |
+| 1.0784        | 1.74  | 200  | 1.1708          | 53.1291 | 27.9056 | 44.2609 | 48.6883   | 26.03   |
+| 1.0215        | 2.17  | 250  | 1.1755          | 53.1512 | 27.9475 | 44.1442 | 48.4619   | 27.57   |
+| 1.0294        | 2.61  | 300  | 1.1711          | 53.4402 | 28.0126 | 44.5454 | 48.6432   | 25.9033 |
+| 1.0016        | 3.04  | 350  | 1.1718          | 53.9395 | 28.3087 | 45.191  | 49.2773   | 26.6133 |
+| 0.9576        | 3.48  | 400  | 1.1741          | 53.9004 | 28.3243 | 45.0911 | 48.9182   | 26.33   |
+| 0.9739        | 3.91  | 450  | 1.1754          | 53.7049 | 28.419  | 44.8946 | 48.8708   | 27.2433 |
+| 0.9505        | 4.35  | 500  | 1.1781          | 53.7142 | 28.1758 | 44.8324 | 48.9498   | 26.8667 |
+| 0.9993        | 4.78  | 550  | 1.1784          | 53.87   | 28.2211 | 44.893  | 49.1074   | 27.2167 |
+
+
+### Framework versions
+
+- Transformers 4.27.0.dev0
+- Pytorch 2.0.0.dev20230130+cu118
+- Datasets 2.9.0
+- Tokenizers 0.13.2

config.json

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+  "vocab_size": 32128
+}

generation_config.json

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